i. Technical Field
This invention pertains to the field of high-speed communications, and more specifically, to signal recovery systems and methods.
ii. Background Art
High-speed communication is a primary focus in the computer and information fields. High-speed communication is desirable in internal networks, external networks, chip-to-chip communications, and any other application in which large amounts of data must be transferred quickly. In a typical local area network, Ethernet connections provide data rates of between 10 Mbps and 100 Mbps. However, this bandwidth is quickly becoming insufficient for modern applications. Data rates in the gigabit range are more optimal for modern applications. Despite the limitations of Ethernet technology, it still provides advantages over competing solutions, including simplicity, low cost, network reliability, availability of management tools, and a high marketplace acceptance. Therefore, a solution to providing higher bandwidth should be preferably compatible with Ethernet technology to be most effective. An IEEE standard has been promulgated for using Ethernet technology for gigabit applications. FIG. 1 illustrates a simplified block diagram of the functional elements of gigabit Ethernet over copper protocol, as defined in the IEEE standard IEEE Std 802.3ab, approved Jun. 28, 1999. The Media Access Control (MAC) layer 112 arbitrates transmission among all nodes attached to the network. It supports both half and full duplex (transmission/reception) operations. The Gigabit Media Independent Interface (GMII) 108 is a digital interface for carrying unencoded data over separate transmit and receive paths. It connects the MAC 112 to various Gigabit Ethernet physical layer components (such as copper). The 1000 Base-T Encoder/Decoder 104 codes and decodes the signals to be sent and received over the physical layer. Finally, the 1000 Base-T Transceiver 100 contains the physical transmitter and receiver used to transmit and receive the high data rate transmissions. The transceiver 100 is coupled to the physical transmission medium.
FIG. 2 illustrates a block diagram of the IEEE-specified transceiver 100. A receiver 200 and a transmitter 204 are coupled to a resistive hybrid 208. The resistive hybrid 208 enables bidirectional transmission over single wire pairs by filtering out the transmit signal from interfering with other signals received by the receiver 200. The receipt of the transmit signal at the receiver 100 is called near-echo. As there are four pairs of wires for a category-5 cable, four sets of the components illustrated in FIG. 2 are used.
The most widely deployed cabling system for local area networks is unshielded twisted pair legacy Category 5 copper wiring. Therefore, a receiver enabling high bandwidth transmission preferably accounts for this existing physical infrastructure and its inherent signal impairments. Transmitting a 1000 Mb/s or higher data stream over four pairs of Category 5 unshielded twisted pair cables introduces several channel impairments that were not present or as significant when 10 Mb/s or 100 Mb/s data streams were being transmitted over the Ethernet. These impairments include signal attenuation, i.e., the signal loss due to cabling from transmitter to receiver; echo, which occurs when transmit and receive signals occupy the same wire pair and interfere with each other; noise and intersymbol interference, defined as any unwanted disturbance in the communication channel; and crosstalk, which arises from close coupling of adjacent wire pairs. All of these impairments lead to degradation of the signal quality. Digital signal processing techniques are typically used to address these impairments, including through the use of adaptive filters in a receiver to eliminate intersymbol interference due to attenuation, adaptive filters for echo canceling, and adaptive filters for crosstalk elimination.
FIG. 3 illustrates the IEEE standard implementation of the receiver 200. A received signal 301 is received over one of the twisted pairs into the resistive hybrid 208. Next, the analog receive filter 300 receives the analog signal and filters out general noise. Then, the received analog signal is converted into a digital signal through a analog-to-digital converter 305, through the input of a clock recovery unit 308 that derives a clock signal from the received signal as input from the analog-to-digital converter 305 and adder 316. The clock recovery unit 308 receives the signal to generate the clock. The clock recovery unit 308 synchronizes the receiver to the carrier frequency. Then, the digital linear feedforward equalizer 312 eliminates any intersymbol interference. The output of the digital linear feedforward equalizer 312 is fed to an adder 316, which also receives the outputs from four other filters. The other filters provide crosstalk and echo compensation. An echo canceller 320 receives the signal 301 and provides a value that indicates the error introduced from the reflection of the signal transmitted from the transmitter 204 reflected back off the destination. Crosstalk canceller 324(1) receives a signal 302 transmitted across one of the other twisted pair. The crosstalk canceller 324(1) produces a value indicating the error introduced from the coupling of the twisted pair carrying signal 302 to the twisted pair carrying signal 301. The other crosstalk cancellers 324(2), 324(3) produce values indicating the error introduced from the coupling of the other twisted pairs. The number of taps per channel required for each of these filters have been shown to be between 8 and 16 for the Feed Forward Equalizer, 19 and 14 for the Decision Feedback Equalizer, 70 and 80 for the Crosstalk Cancellers, and 60 and 120 for the Echo Canceller. The adder 316 then provides a composite signal 306 that represents the received signal 301 filtered for the above noise factors. The output 306 of the adder 316 is fed to a Viterbi decoder 328 that uses coding to help recover transmitted symbol in the presence of high noise. The output of the Viterbi decoder 328 is the recovered data 307. The output 307 is also fed to a decision feedback equalizer 332 that adjusts the adder 316 to compensate for any error detected in transmission.
The IEEE standard does not specify the implementation of the digital filters 312, 320, 324, and 332. Existing filters require extensive training to learn the correct filter parameters that will overcome the channel impairments. In these filters, a sample of the input signal is used in a training mode at the receiver 200 to determine the characteristics of the channel, and to compensate for those characteristics. These filters then use a variety of digital signal processing techniques to generate the channel characteristics. However, to ensure that the channel characterization remains accurate, the training of the filter must be repeated each time a link is lost, the channel dynamics change, or the noise characteristics vary. Thus, networks that rely on training waste valuable bandwidth, as the time required for training is used at the expense of actual transmission time.
In an attempt to eliminate the requirement of training, other systems use receivers having blind adaptive filters. Blind adaptive filters use only the amplitude of the input signal to recreate channel characteristics. FIG. 4 illustrates a block diagram of a blind adaptive filter. A transmitter 400 at a remote site transmits a signal st through a channel 404 to an equalizer 408. Channel 404 adds noise and intersymbol interference to the signal st resulting in a corrupted signal xt. The equalizer 408 is designed to recover the input signal st from the signal corrupted by intersymbol interference and noise xt. To determine the parameters of the equalizer 408, an amplitude square extractor 412 is used to provide the square of the amplitude of the received signal xt to the blind adaptive mechanism 416. The blind adaptive mechanism 416 uses the squared amplitude to generate characteristics of the channel 404. The channel characteristics are generated to emulate the noise and the intersymbol interference added to the signal st during transmission. Once the channel characteristics are known, the equalizer 408 can be adjusted to compensate for the channel characteristics.
Many practical and popular digital communication systems use blind adaptive filters. In these systems, the amplitude of the signal throughout the transmission link is supposed to remain constant, and therefore its use does not require special a priori knowledge or measurements of the input signal. However, determining the characteristics of the channel 404 from using only the amplitude of the input signal is extremely difficult. Blind adaptive systems generate multiple possible solutions, and provide no basis for choosing between the multiple solutions. In blind adaptive systems, the channel parameters must be reproduced from the amplitude squared equation: et=|yt|2xe2x88x921. However, since only the amplitude is known, this equation is difficult to solve for channel parameters because there is no known closed form expression of it in terms of W, where W is a vector representing the weights of the equalizer. In conventional systems, an approximation was used to determine the value of W. The approximation used determines Was Wt=Wtxe2x88x921xe2x88x92xcexcytxe2x88x921Xtxe2x88x921etxe2x88x921, where the vector Xt is the vector of the n received sequence samples. The innovation term xcexcytxe2x88x921Xtxe2x88x921etxe2x88x921, was designed to generate solutions for W from the constant amplitude equation. However, the approximation parameter generates multiple solutions for possible weights to be used for the equalizer, and did not provide a basis for distinguishing between them. Therefore, these systems are less accurate and less reliable than those which use a training mode. However, as discussed above, systems using training modes waste bandwidth and are more costly than the blind adaptive filter systems.
Thus, a system is needed which overcomes channel impairments and provides for high-speed data communication without requiring the use of training, and provides single value accurate solutions.
In accordance with the present invention, a system, method, and apparatus of characterizing channel characteristics and recovering an original signal without the use of a training mode that provides single-valued solutions is disclosed. In accordance with the present invention, a received signal is sent to an equalizer (508) which compensates for intersymbol interference and noise added to the transmitted signal st during transmission. To accurately determine the weights of the equalizer (508), the output of the equalizer (508) is transmitted to an amplitude square extractor (512) to generate a value that approximates the amplitude of the originally transmitted signal st. Then, a forward-mapping module (516) maps the amplitude value from the n-dimensional space st of the amplitude value to an augmented space having, in a preferred embodiment, n2 dimensions. In the augmented space, an augmented space blind adaptation mechanism (520) is applied to generate a single-valued channel characteristic value in terms of an augmented space variable. Then, a backward-mapping module (524) is applied to generate the optimal weights for the equalizer (508) allowing an accurate recovery of the original signal. The principles of the present invention can be applied to generate all of the filters required in high-speed data communications, and can be used for any other system in which channel characteristics are desired.